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IJON
2002

On the generative probability density model in the self-organizing map

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On the generative probability density model in the self-organizing map
The Self-Organizing Map, SOM, is a widely used tool in exploratory data analysis. A major drawback of the SOM has been the lack of a theoretically justified criterion for model selection. Model complexity has a decisive effect on the reliability of visual data analysis, which is a main application of the SOM. In particular, independence of variables cannot be observed unless generalization of the model is good. We describe the maximum likelihood probability density model which follows from the SOM training rule, and show how the density model can be applied to choosing the correct model complexity, based on the method of maximum likelihood.
Timo Kostiainen, Jouko Lampinen
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Where IJON
Authors Timo Kostiainen, Jouko Lampinen
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